Code division multiple access (CDMA) has been extensively used in such applications as cellular and satellite communications. CDMA signals increase the spectrum required for the transmission of a particular data rate by modulating each information symbol with a spread spectrum code having a rate larger than the data rate. The same spreading code is used for each information symbol. Typically, the spreading code comprises of a few tens or a few hundreds elements, called chips. To decrease the correlations among spreading codes assigned to different users and thereby reduce the interference among the different users, the data stream after spreading is typically scrambled with a pseudonoise (PN) code that is generated serially and cyclically and has a larger period than the spreading code. Examples of such CDMA signal spreading are the schemes used by the 3rd Generation Partnership Project (3GPP) and 3GPP2 communication systems and their respective evolutions of High Speed Downlink Packet Access (HSDPA) and 1x-EVDV.
With CDMA, the signals from all users simultaneously occupy the same frequency band. The receiver discriminates the multiple signals by exploiting the properties of the spreading and scrambling codes that are applied to the signal of each user. The receiver attempts to match in time with the codes of the desired signal a replica of those spreading and scrambling codes. Only then the demodulation result is meaningful; otherwise it appears noise-like. Thus, if the arriving signals have different codes or different code offsets, they can be discriminated at the receiver.
The conventional receiver structure for CDMA signals is the well-known Rake receiver. The Rake receiver performs maximal ratio combining by multiplying each signal path with the conjugate of the corresponding channel estimate and then adding the individual results. The channel estimate is typically obtained through the use of a pilot signal. Alternatively, for Quadrature Amplitude Modulation (QAM) or M-ary Phase Shift Keying (MPSK) type modulation schemes, alternative receivers structures such as an equalizer or an interference canceller may be used to avoid the shortcomings of the Rake receiver when the signal is transmitted through a multipath-fading channel.
In order to successfully demodulate the data signal, the constellation of the corresponding data symbols after demodulation with any receiver type (Rake, equalizer, interference canceller) must have the distribution dictated by the particular modulation scheme. To achieve this objective, the data needs to be appropriately scaled. For example, for a Rake receiver or for an interference canceller incorporating the Rake receiver, the output of the maximal ratio combiner (MRC) must be scaled by the ratio of the data-to-pilot signal power. The same is true for an equalizer receiver using the pilot signal for training. The appropriate power ratio may be signaled by the transmitter, or alternatively, be computed at the receiver. The second option is preferable, if it can be implemented and does not lead to considerable performance losses, since it avoids the bandwidth consumption that would be otherwise needed for the signaling of the pilot-to-data power ratio. Computation of the data-to-pilot power ratio at the receiver is required by HSDPA and may be used for estimation of the data signal SNR, the noise variance, or for power control purposes as required by 3GPP and 3GPP2.
The conventional approach of measuring the data-to-pilot power ratio at the receiver is to compute the individual signal power or Signal-to-Noise Ratio (SNR) for both pilot and data signals. This requires measurement of the received signal over several data periods to obtain the necessary quantities (signal power or SNR) and thereby introduces processing delay. This latency in the demodulation process may place additional constraints in the receiver's design when a particular communications application is sensitive to delays or when feedback is required from the receiver in a timely manner. Moreover, there is some additional receiver complexity involved with the signal power or SNR estimation process. Also, the robustness of the previous estimates may not be good enough to ensure small performance losses under all possible channel conditions. This is because the signal may be in fading or there may be signal paths that are too weak to be identified or to close to be discriminated. Such situations may affect the accuracy of the power or SNR estimates and degrade the performance of a receiver relying on them to perform demodulation of the received signal.